context safety score
A score of 33/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
encoded payload
suspicious base64-like blobs detected in page content
js obfuscation
JavaScript uses eval() with String.fromCharCode — common obfuscation
js obfuscation
JavaScript uses eval(atob()) — base64-encoded payload execution
obfuscated code
The page contains a heavily obfuscated JavaScript payload: a single script block with a 288-element string array (a0T), a custom base64/rot decoder (a0N), single-letter function names, and an eval() call that executes dynamically loaded module code fetched via XMLHttpRequest. The obfuscation prevents static analysis of the full behavior and is consistent with evasion of security scanners. (location: page.html, <script> block, function a0T / a0N / eval() at ~line 2)
brand impersonation
The domain s7cdn.online presents itself as a CDN or infrastructure endpoint for www.s7.ru (S7 Airlines, a major Russian carrier). The base64-encoded settings string decodes to include 'www.s7.ru' as the target domain. The domain name 's7cdn.online' closely mimics legitimate S7 infrastructure (e.g., cdn.s7.ru) to appear trustworthy while being a separate, unaffiliated .online TLD registration. (location: metadata.json domain field; page.html window.ctx settings parameter decoding to www.s7.ru)
hidden content
The element #client-container is hidden via 'display:none' by default and is only revealed dynamically by JavaScript. This container holds the IP address display, request ID, and a 'Download error report' link (shadowLink) whose href is set programmatically. The true destination of the shadowLink download is not visible in static HTML and is controlled entirely by obfuscated JS. (location: page.html, CSS rule '#client-container{display:none}', and <a id='shadowLink'> element)
obfuscated code
Challenge module JavaScript files are loaded at runtime from a path containing a base64-encoded segment that decodes to 'hello, human' (/ngenix-aGVsbG8sIGh1bWFu/bot-challenge/modules/). These modules are injected into the DOM and executed, including via eval(), meaning arbitrary code can be delivered post-load without it being present in the static page source. This is a classic multi-stage payload delivery pattern. (location: page.html window.ctx challenge_modules_location and eval() in main script block)
social engineering
The page displays a fake browser verification screen in Russian ('Your browser will be checked now. Please wait for the page to load.') with UI elements showing the visitor's IP address and request ID, and a 'Download error report' link. This pattern is commonly used in social engineering to establish legitimacy and induce the user to wait passively or click a download link, potentially delivering malware. (location: page.html <h1 id='title'> and <h3 id='description'> elements; <a id='shadowLink'>)
curl https://api.brin.sh/domain/s7cdn.onlineCommon questions teams ask before deciding whether to use this domain in agent workflows.
s7cdn.online currently scores 33/100 with a suspicious verdict and low confidence. The goal is to protect agents from high-risk context before they act on it. Treat this as a decision signal: higher scores suggest lower observed risk, while lower scores mean you should add review or block this domain.
Use the score as a policy threshold: 80–100 is safe, 50–79 is caution, 20–49 is suspicious, and 0–19 is dangerous. Teams often auto-allow safe, require human review for caution/suspicious, and block dangerous.
brin evaluates four dimensions: identity (source trust), behavior (runtime patterns), content (malicious instructions), and graph (relationship risk). Analysis runs in tiers: static signals, deterministic pattern checks, then AI semantic analysis when needed.
Identity checks source trust, behavior checks unusual runtime patterns, content checks for malicious instructions, and graph checks risky relationships to other entities. Looking at sub-scores helps you understand why an entity passed or failed.
brin performs risk assessments on external context before it reaches an AI agent. It scores that context for threats like prompt injection, hijacking, credential harvesting, and supply chain attacks, so teams can decide whether to block, review, or proceed safely.
No. A safe verdict means no significant risk signals were detected in this scan. It is not a formal guarantee; assessments are automated and point-in-time, so combine scores with your own controls and periodic re-checks.
Re-check before high-impact actions such as installs, upgrades, connecting MCP servers, executing remote code, or granting secrets. Use the API in CI or runtime gates so decisions are based on the latest scan.
Learn more in threat detection docs, how scoring works, and the API overview.
Assessments are automated and may contain errors. Findings are risk indicators, not confirmed threats. This is a point-in-time assessment; security posture can change.
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